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Fundamental Statistics for the Social and Behavioral Sciences
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Fundamental Statistics for the Social and Behavioral Sciences

Second Edition
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October 2018 | 712 pages | SAGE Publications, Inc
Fundamental Statistics for the Social and Behavioral Sciences, Second Edition, places statistics within the research process, illustrating how they are used to answer questions and test ideas. Students learn not only how to calculate statistics, but also how to interpret and communicate the results of statistical analyses in light of a study’s research hypothesis. Featuring accessible writing and well-integrated research examples, the book gives students a greater understanding of how research studies are conceived, conducted, and communicated.

The Second Edition includes a new chapter on regression; covers how collected data can be organized, presented and summarized; the process of conducting statistical analyses to test research questions, hypotheses, and issues/controversies; and examines statistical procedures used in research situations that vary in the number of independent variables in the study. Every chapter includes learning checks, such as review questions and summary boxes, to reinforce the content students just learned, and exercises at the end of every chapter help assess their knowledge. 

Also new to the Second Edition -- animated video tutorials! Watch the demo video from Chapter 2 now!

Corrections: there are a small number of corrections for the text's Appendix posted here.
 
About the Author
 
Preface to the Second Edition
 
Preface to the First Edition
 
Acknowledgments
 
Companion Site
 
Chapter 1. Introduction to Statistics
1.1 What Is Statistics?

 
1.2 Why Learn Statistics?

 
1.3 Introduction to the Stages of the Research Process

 
1.4 Plan of the Book

 
1.5 Looking Ahead

 
1.6 Summary

 
1.7 Important Terms

 
1.8 Exercises

 
 
Chapter 2. Examining Data: Tables and Figures
2.1 An Example From the Research: Winning the Lottery

 
2.2 Why Examine Data?

 
2.3 Examining Data Using Tables

 
2.4 Grouped Frequency Distribution Tables

 
2.5 Examining Data Using Figures

 
2.6 Examining Data: Describing Distributions

 
2.7 Looking Ahead

 
2.8 Summary

 
2.9 Important Terms

 
2.10 Formulas Introduced in This Chapter

 
2.11 Using IBM SPSS Software

 
2.12 Exercises

 
 
Chapter 3. Measures of Central Tendency
3.1 An Example From the Research: The 10% Myth

 
3.2 Understanding Central Tendency

 
3.3 The Mode

 
3.4 The Median

 
3.5 The Mean

 
3.6 Comparison of the Mode, Median, and Mean

 
3.7 Measures of Central Tendency: Drawing Conclusions

 
3.8 Looking Ahead

 
3.9 Summary

 
3.10 Important Terms

 
3.11 Formulas Introduced in This Chapter

 
3.12 Exercises

 
 
Chapter 4. Measures of Variability
4.1 An Example From the Research: How Many “Sometimes” in an “Always”?

 
4.2 Understanding Variability

 
4.3 The Range

 
4.4 The Interquartile Range

 
4.5 The Variance (s2)

 
4.6 The Standard Deviation (s)

 
4.7 Measures of Variability for Populations

 
4.8 Measures of Variability for Nominal Variables

 
4.9 Measures of Variability: Drawing Conclusions

 
4.10 Looking Ahead

 
4.11 Summary

 
4.12 Important Terms

 
4.13 Formulas Introduced in This Chapter

 
4.14 Using SPSS

 
4.15 Exercises

 
 
Chapter 5. Normal Distributions
5.1 Example: SAT Scores

 
5.2 Normal Distributions

 
5.3 The Standard Normal Distribution

 
5.4 Applying z-Scores to Normal Distributions

 
5.5 Standardizing Frequency Distributions

 
5.6 Looking Ahead

 
5.7 Summary

 
5.8 Important Terms

 
5.9 Formulas Introduced in This Chapter

 
5.10 Exercises

 
 
Chapter 6. Probability and Introduction to Hypothesis Testing
6.1 A Brief Introduction to Probability

 
6.2 Example: Making Heads or Tails of the Super Bowl

 
6.3 Introduction to Hypothesis Testing

 
6.4 Issues Related to Hypothesis Testing: An Introduction

 
6.5 Looking Ahead

 
6.6 Summary

 
6.7 Important Terms

 
6.8 Formulas Introduced in This Chapter

 
6.9 Exercises

 
 
Chapter 7. Testing One Sample Mean
7.1 An Example From the Research: Do You Read Me?

 
7.2 The Sampling Distribution of the Mean

 
7.3 Inferential Statistics: Testing One Sample Mean (s Known)

 
7.4 A Second Example From the Research: Unique Invulnerability

 
7.5 Introduction to the t-Distribution

 
7.6 Inferential Statistics: Testing One Sample Mean (s Not Known)

 
7.7 Factors Affecting the Decision About the Null Hypothesis

 
7.8 Looking Ahead

 
7.9 Summary

 
7.10 Important Terms

 
7.11 Formulas Introduced in This Chapter

 
7.12 Using SPSS

 
7.13 Exercises

 
 
Chapter 8. Estimating the Mean of a Population
8.1 An Example From the Research: Salary Survey

 
8.2 Introduction to the Confidence Interval for the Mean

 
8.3 The Confidence Interval for the Mean (s Not Known)

 
8.4 The Confidence Interval for the Mean (s Known)

 
8.5 Factors Affecting the Width of the Confidence Interval for the Mean

 
8.6 Interval Estimation and Hypothesis Testing

 
8.7 Looking Ahead

 
8.8 Summary

 
8.9 Important Terms

 
8.10 Formulas Introduced in This Chapter

 
8.11 Using SPSS

 
8.12 Exercises

 
 
Chapter 9. Testing the Difference Between Two Means
9.1 An Example From the Research: You Can Just Wait

 
9.2 The Sampling Distribution of the Difference

 
9.3 Inferential Statistics: Testing the Difference Between Two Sample Means

 
9.4 Inferential Statistics: Testing the Difference Between Two Sample Means (Unequal Sample Sizes)

 
9.5 Inferential Statistics: Testing the Difference Between Paired Means

 
9.6 Looking Ahead

 
9.7 Summary

 
9.8 Important Terms

 
9.9 Formulas Introduced in This Chapter

 
9.10 Using SPSS

 
9.11 Exercises

 
 
Chapter 10. Errors in Hypothesis Testing, Statistical Power, and Effect Size
10.1 Hypothesis Testing vs. Criminal Trials

 
10.2 An Example From the Research: Truth or Consequences

 
10.3 Two Errors in Hypothesis Testing: Type I and Type II Error

 
10.4 Controlling Type I and Type II Error

 
10.5 Measures of Effect Size

 
10.6 Looking Ahead

 
10.7 Summary

 
10.8 Important Terms

 
10.9 Formulas Introduced in This Chapter

 
10.10 Exercises

 
 
Chapter 11. One-Way Analysis of Variance (ANOVA)
11.1 An Example From the Research: It’s Your Move

 
11.2 Introduction to Analysis of Variance (ANOVA)

 
11.3 Inferential Statistics: One-Way Analysis of Variance (ANOVA)

 
11.4 A Second Example: The Parking Lot Study Revisited

 
11.5 Analytical Comparisons Within the One-Way ANOVA

 
11.6 Looking Ahead

 
11.7 Summary

 
11.8 Important Terms

 
11.9 Formulas Introduced in This Chapter

 
11.10 Using SPSS

 
11.11 Exercises

 
 
Chapter 12. Two-Way Analysis of Variance (ANOVA)
12.1 An Example From the Research: Vote—or Else!

 
12.2 Introduction to Factorial Research Designs

 
12.3 The Two-Factor (A × B) Research Design

 
12.4 Introduction to Analysis of Variance (ANOVA) for the Two-Factor Research Design

 
12.5 Inferential Statistics: Two-Way Analysis of Variance (ANOVA)

 
12.6 Investigating a Significant A × B Interaction Effect: Analysis of Simple Effects

 
12.7 Looking Ahead

 
12.8 Summary

 
12.9 Important Terms

 
12.10 Formulas Introduced in This Chapter

 
12.11 Using SPSS

 
12.12 Exercises

 
 
Chapter 13. Correlation
13.1 An Example From the Research: It’s Good for You!

 
13.2 Introduction to the Concept of Correlation

 
13.3 Inferential Statistics: Pearson Correlation Coefficient

 
13.4 Correlating Two Sets of Ranks: The Spearman Rank-Order Correlation

 
13.5 Correlational Statistics vs. Correlational Research

 
13.6 Looking Ahead

 
13.7 Summary

 
13.8 Important Terms

 
13.9 Formulas Introduced in This Chapter

 
13.10 Using SPSS

 
13.11 Exercises

 
 
Chapter 14. Linear Regression and Multiple Correlation
14.1 Predicting One Variable From Another: Linear Regression

 
14.2 Correlation With Two or More Predictors: Introduction to Multiple Correlation and Regression

 
14.3 Looking Ahead

 
14.4 Summary

 
14.5 Important Terms

 
14.6 Formulas Introduced in This Chapter

 
14.7 Using SPSS

 
14.8 Exercises

 
 
Chapter 15. Chi-Square
15.1 An Example From the Research (One Categorical Variable): Are You My Type?

 
15.2 Introduction to the Chi-Square Statistic

 
15.3 Inferential Statistic: Chi-Square Goodness-of-Fit Test

 
15.4 An Example From the Research (Two Categorical Variables): Seeing Red

 
15.5 Inferential Statistic: Chi-Square Test of Independence

 
15.6 Parametric and Nonparametric Statistical Tests

 
15.7 Looking Ahead

 
15.8 Summary

 
15.9 Important Terms

 
15.10 Formulas Introduced in This Chapter

 
15.11 Using SPSS

 
15.12 Exercises

 
 
Tables
 
Appendix: Review of Basic Mathematics
 
Glossary
 
References
 
Index

Supplements

Instructor edge site

SAGE edge for Instructors supports your teaching by making it easy to integrate quality content and create a rich learning environment for students.

  • Test banks in Word format and ExamView provide a diverse range of pre-written options as well as the opportunity to edit any question and/or insert your own personalized questions to effectively assess students’ progress and understanding.
  • Sample course syllabi for semester and quarter courses provide suggested models for structuring your courses.
  • Editable, chapter-specific PowerPoint® slides offer complete flexibility for creating a multimedia presentation for your course. 
  • Multimedia content includes original SAGE videos featuring tutorials with author Howard T. Tokunaga that bring concepts to life and appeal to diverse learners.
  • Lecture notes summarize key concepts by chapter to help you prepare for lectures and class discussions.
  • Course cartridge for easy LMS integration
  • Answers to even-numbered questions from the text help facilitate grading.
  • SPSS datasets are available for use with exercises from the text.
Student edge site

SAGE edge for Students provides a personalized approach to help students accomplish their coursework goals in an easy-to-use learning environment.

  • Mobile-friendly eFlashcards strengthen understanding of key terms and concepts. 
  • Mobile-friendly practice quizzes allow for independent assessment by students of their mastery of course material. 
  • Multimedia content includes original SAGE animated tutorial videos bring concepts to life and appeal to diverse learners.
  • SPSS datasets are available for use with exercises from the text.
     

“I think this is some of the best explanation for these concepts that I have read.”

JoEllen Pederson
Longwood University

“I appreciate the structures, the simplicity in the language, the clarity and the ability to pull material that is appropriate for college level courses.”

Cristine Rego
Fleming College

“I think the author has a strong command and grasp of the material which he demonstrates by providing students with a multitude of examples and formulas that are easy to understand and broken down into digestible portions for students to absorb at their own pace. The writing style of the author is excellent…He spends a significant amount of time decomposing and deconstructing complex ideas related to the measures of central tendency for both novice and expert students of statistics in a user-friendly and approachable tone.”

Keith Feigenson
Albright College

“The writing style is nice and easy to follow.”

 
Timothy Victor
University of Pennsylvania

Howard T. Tokunaga

Howard T. Tokunaga is Professor of Psychology at San Jose State University, where he serves as Coordinator of the MS Program in Industrial/Organizational (I/O) Psychology and teaches undergraduate and graduate courses in statistics, research methods, and I/O psychology. He received his bachelor’s degree in psychology at UC Santa Cruz and his PhD in psychology at UC Berkeley. In addition to his teaching, he has consulted with a number of public-sector and private-sector organizations on a wide variety of management and human resource issues. He is coauthor (with G. Keppel) of Introduction to Design and Analysis: A Student’s Handbook. More About Author

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ISBN: 9781506377483
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